Applications of artificial intelligence to the diagnostic evaluation of infectious keratitis

项目摘要/摘要 本K23提案旨在开发和评估人工智能(AI)在诊断中的应用 对传染性角膜炎的调查，这是全世界失明的主要原因。这将通过以下方式实现 三个具体目标：1)开发和评估人工智能模型，以确定培养证实的传染性疾病的病原学 来自现有临床照片数据库的角膜炎；2)在真实的- 世界上基于人群的角膜溃疡样本；以及3)开发和评估额外的人工智能模型 真菌性角膜炎的自动显微镜诊断。在SA#1中开发的AI模型将使用 临床摄影数据库(培养阳性溃疡数据库)来自美国国立卫生研究院资助的几个临床 过去几十年进行的感染性角膜炎(SCUT、Mutt I&II、Clair和Malin)试验 作为弗朗西斯·I·普罗科特基金会和阿拉文德眼科医院#年国际合作的一部分 印度。该模型的性能将与人类专家在培养证实的传染性病例上进行比较 角膜炎。第二个角膜溃疡的影像和临床数据储存库(Madurai数据库) 目前正在开发中的人工智能模型将用于外部验证SA#1中开发的人工智能模型(通过估计其 在真实世界样本中的敏感性和特异性)，并在SA#3中训练AI模型。 为了实现研究目标，我们在凯西眼科研究所、 普罗科特基金会和阿拉文。这提供了一个前所未有的机会来利用我的专业知识 凯西在人工智能和计算机视觉眼科疾病诊断方面的导师， 普罗科特世界级教师在流行病学、生物统计学和感染性角膜炎方面的专业知识，以及 阿拉文德无与伦比的传染性角膜炎和数据收集基础设施。此协作 将促进精心设计和验证的人工智能模型的开发，这些模型将指导早期指导 抗菌治疗和改善感染性角膜炎的视力结果。 我的主要职业目标是将自己确立为一名独立的临床科学家，在 技术创新与国际公共卫生的接口。我的公共卫生硕士，医学训练，还有 研究经验使我在公共卫生、临床和外科方面打下了坚实的基础 角膜感染的管理，以及医学信息学。在过去九个月的K12支持中，我有 开始开发机器学习和数据科学方面的专业知识，建立了我将建立的基础 在此K23授权期内。人工智能在医疗保健问题上的成功应用需要 涉及临床医生、人工智能方法学家、信息学家和公共卫生专家的多学科方法。这 K23将使我能够在这些学科中的每一个方面积累技能和专业知识，并成为领导的有利条件 未来几年的这场运动。

PROJECT SUMMARY/ABSTRACT This K23 proposal aims to develop and evaluate applications of artificial intelligence (AI) to the diagnostic investigation of infectious keratitis, a major cause of blindness worldwide. This will be accomplished through three specific aims: 1) Develop and evaluate an AI model to identify the etiology of culture-proven infectious keratitis from an existing database of clinical photographs; 2) Externally validate model performance in a real- world, population-based sample of corneal ulcers; and 3) Develop and evaluate an additional AI model for automated microscopic diagnosis of fungal keratitis. The AI model developed in SA#1 will be trained using a clinical photography database (the Culture Positive Ulcer Database) collated from several NIH funded clinical trials for infectious keratitis (SCUT, MUTT I & II, CLAIR, and MALIN) conducted over the past several decades as part of the international collaboration between the Francis I. Proctor Foundation and Aravind Eye Hospital in India. This model's performance will be compared against human experts on culture-proven cases of infectious keratitis. A second repository of imaging and clinical data from corneal ulcers (the MADURAI database) currently in development will be used to externally validate the AI model developed in SA#1 (by estimating its sensitivity and specificity in a real-world sample) and to train the AI model in SA#3. To accomplish these research goals, we have established an international collaboration between the Casey Eye Institute, the Proctor Foundation, and Aravind. This provides an unprecedented opportunity to leverage the expertise of my mentors at Casey in artificial intelligence and computer vision-enabled diagnosis of ophthalmic diseases, the expertise of the world-class faculty at Proctor in epidemiology, biostatistics, and infectious keratitis, and the unparalleled volume of infectious keratitis and infrastructure for data collection at Aravind. This collaboration will facilitate the development of carefully designed and validated AI models which will guide earlier directed antimicrobial therapy and improve visual outcomes in infectious keratitis. My primary career goals are to establish myself as an independent clinician scientist performing research at the interface of technological innovation and international public health. My MPH, medical training, and research experience have allowed me to develop a strong foundation in public health, the clinical and surgical management of corneal infections, and medical informatics. Over the past nine months of K12 support I have begun developing expertise in machine learning and data science, establishing a foundation which I will build upon during this K23 award period. The successful application of AI to health care problems requires a multidisciplinary approach involving clinicians, AI methodologists, informaticists, and public health experts. This K23 will allow me to build skills and expertise in each of these disciplines and become well positioned to lead this movement in the coming years.